摘要
销售及需求预测是现代供应链的重要构成,有参考价值的预测能给采购和计划环节带来时间上的优势,并节约了物流仓储环节的成本,从而提高整个供应链的效率。文中介绍了在预测中常用的指数平滑法,通过对历史数据以时间序列为标准进行权重分配,并综合考虑发展趋势和季节等多重因素,从而得到的较为合理的,有一定参考价值的预测数据。
Sales and demand forecast is a key component in modern supply chain. Useful forecast result brings buffering time for procurement and planning, and it saves the cost in logistics and warehousing as well. Therefore, reasonable forecast result can enhance the efficiency of the whc,le supply chain. We introduce a common forecasting model below, which is known as Exponential Smoothing. Exponential Smoothing weights historical data according to time series. Other factors such as trend and seasonality are considered in that model as well to ensure the rationality and the value of reference of the forecast result.
出处
《物流工程与管理》
2011年第5期77-78,共2页
Logistics Engineering and Management
关键词
需求预测
需求管理
指数平滑法
demand forecast
demand management
exponential smoothing
